SuccessfulKoala55 Thank you for the response! Let me elaborate a bit to check if I understand this correctly.
We have a time-consuming task T based on optimization for parameters. We want to run hyperparameter optimization for T, suppose that we want to run it for 100 sets of parameters.
We want to leverage the fact that we have n machines to make the work parallel.

So for that we use https://clear.ml/docs/latest/docs/references/sdk/hpo_optimization_hyperparameteroptimizer/ , we run Agents on n machines and we put those tasks to queues and tasks are run on n machines.

Do I understand that correctly? Also another question - suppose, that we want to stop the search when some metric is satisfied (for example some loss value is smaller than THRESHOLD). Is there such option in ClearML?